How you type or move a mouse could help detect whether you have a serious disease like Parkinson’s.

A Duke University doctor working with
Microsoft
researchers sifted through data on the physical movements of computer users that came from millions of internet searches. Their study found links between some behaviors—such as tremors when using a mouse, repeat queries and average scrolling velocity—and Parkinson’s disease. They used artificial intelligence, or a computer analysis, to identify which of the metrics separated a control group from those searching for Parkinson’s disease symptoms.

The research is part of a trend sweeping health care: the use of artificial intelligence (AI) to help better diagnose and treat patients. The goal is to capture information by monitoring their everyday movements and behaviors. This could yield insights never possible in a pre-digital age. It also, in the case of commercial companies, raises questions about how best to protect the privacy of research subjects.

AI gives researchers a chance to get much more real-time information on how people function, says
Jeffrey Kaye,
director of the Oregon Center for Aging and Technology, part of Oregon Health & Science University.

“Right now clinicians basically use the old-fashioned way of gathering information,” he says. “It’s like medical anthropology. You’re trying to detect things that are happening based on really very little historical data.”

Doctors say what they call digital biomarkers could be especially useful for brain disorders like Parkinson’s and Alzheimer’s.

“Both of these conditions in their very early stages can be very hard to differentiate from a host of benign conditions, so the misdiagnosis rate is high,” says
Murali Doraiswamy,
director of the neurocognitive disorders program at Duke University, who was part of the Microsoft research.

Using a computer keyboard and mouse to monitor one’s function means researchers need no special equipment. Plus, they can capture data over long stretches, Dr. Doraiswamy says. “You can see how someone is changing over time, which might give you greater sensitivity and accuracy in making a diagnosis.”

The study he worked on with Microsoft analyzed more than 31 million user searches on Microsoft’s search engine, Bing, over 18 months. About 700 of the user searches were searching for Parkinson’s disease symptoms, while the remainder were considered the control group. The data were anonymized and can’t be linked back to users, Dr. Doraiswamy says. NPJ Digital Medicine published the results of this research in April.

Photo:
Stuart Bradford

This kind of data-driven research has grown more common.
Adriana Seelye,
a neuropsychologist at the Minneapolis VA Health Care System and Dr. Kaye’s former student, has focused on using sensors in cars and on computers to help detect early Alzheimer’s disease.

“What we’re working on is using the information that these sensors give us to figure out what the most important patterns are that emerge when someone is going from normal, healthy aging to early Alzheimer’s disease,” Dr. Seelye says.

In a study published in 2017 in the journal Alzheimer’s & Dementia, she and co-researchers followed 110 healthy elderly adults for up to three years and six months. They tracked the participants as they did a weekly online health survey. They found 29 people ended up with mild cognitive impairment (MCI), which puts them at risk for developing Alzheimer’s disease. Those with MCI took longer to complete the survey.

Dr. Seelye and co-researchers also studied the mouse usage of 42 elderly adults, 20 of whom had MCI, over one week. That study, published in 2015, found those with MCI made fewer mouse movements and had longer pauses between movements.

She has also studied how people drive using information from the sensors installed in data ports in cars. The data port relays information on the number of trips taken, duration of trips, left turns versus right turns and time spent on the highway versus local roads, among other information.

In a pilot study published in 2017 in the Journal of Alzheimer’s Disease, Dr. Seelye and co-researchers analyzed the driving information of 28 people over an average of about 200 days. They found that those with MCI drove fewer miles and showed less variability in their driving patterns.

Now she’s working on a federally funded study trying to replicate the findings with more than 100 patients followed over four years. The researchers will use sensors to monitor the driving, computer use and medication use of all the participants and then use computational modeling to make predictions off that data. “What is the best combination of variables that will be sensitive to detecting early Alzheimer’s disease?” she asks.

Dr. Doraiswamy of Duke says the next step is to test the digital metric they came up with in the Bing study to see if it would line up with the computer logs of patients already diagnosed with Alzheimer’s or Parkinson’s disease, with their consent.

Microsoft declined to comment on the study. A spokeswoman for Microsoft says Bing users’ search and mouse activity is analyzed in a way that is not directly tied to individual users, which is common industry practice.

Arvind Narayanan,
an assistant professor of computer science at Princeton University who researches and teaches about information privacy and security, says companies routinely collect computer user information such as mouse movements. “Do users know this is going on? I would say this collection of this information is disclosed in a privacy policy,” Dr. Narayanan says. “But it is generally not the case that users read the privacy policy and understand it before using a site.”

Privacy policies are usually vaguely worded, so it can be hard to decipher what the information will be used for, he says. Using the information for medical research without clear notice seems “inappropriate,” he says. “On the other hand, what is an ideal consent model for this kind of surprising use of big data in a medical research context?” Dr. Narayanan says. “I think there are genuinely open questions and people are still working out the answers to these things.”

Dr. Kaye, whose research has used sensors on keyboards and other technology in his studies, says while patient privacy can be a concern, studies have found that patients don’t mind such data going to their doctors, but they may trust commercial entities less.

Dr. Doraiswamy says the Microsoft researchers were able to analyze the data after they were made anonymous with no intent to ever link back to the users.

“So this type of data is generally considered acceptable to analyze because it’s de-identified, so there’s no privacy issues,” says Dr. Doraiswamy.

He notes companies and academic researchers are increasingly analyzing user data to flag for mental health and medical conditions.